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The repository contains code for the following tasks included in A prognostic neural epigenetic signature in high-grade glioma [1]:

Task Description Source
An example run of the signature classifying the neural groups Contains code to run the fitted logistic regression model on an example IDAT run neural classification
DNA methylation deconvolution Code to process and perform DNA methylation deconvolution. Please cite Moss et al. (2018) [2] if you use it. DNAm_deconv
CNV Wrapper to perform copy number variation analysis using Conumee package across multiple groups CNV
Differential methylation probes Differential methylation probes and gene set enrichment between the neural groups DNAm_DMP
Optimal number of clusters Overcluster the clinical cohort to find if cluster size > 2 is significantly separable with respect to overall survival neural_group_over_cluster
Signature classifying the neural groups Contains code to stratify neural groups based on DMP probes between low and neural groups. Include trained logistic regression model neural_group_classification
Mutation analysis Code to generate oncoplot on mutations Oncolplot.ipynb
RNA groups Compare correspondence between RNA GBM subgroups and neural subgroups for paired DNAm-RNA TCGA data TCGA
WGCNA Code to perform WGCNA analysis on paired proteomics data, also includes geneset and cell type enrichment WGCNA_proteomics

References

[1] Drexler, R., Khatri, R., Sauvigny, T. et al. A prognostic neural epigenetic signature in high-grade glioma. Nat Med (2024). https://doi.org/10.1038/s41591-024-02969-w

[2] Moss, J., Magenheim, J., Neiman, D. et al. Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease. Nat Commun 9, 5068 (2018). https://doi.org/10.1038/s41467-018-07466-6

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